Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Silicon23/BERTForDetectingDepression-Twitter2020 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Silicon23/BERTForDetectingDepression-Twitter2020 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Silicon23/BERTForDetectingDepression-Twitter2020")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Silicon23/BERTForDetectingDepression-Twitter2020") model = AutoModelForSequenceClassification.from_pretrained("Silicon23/BERTForDetectingDepression-Twitter2020", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8087704534d3eb57f28d82203d229ae37c7f37d41e8b31e12c187636e752f23f
- Size of remote file:
- 5.18 kB
- SHA256:
- 31bc351639b0d5d9c35e7732fa60f18c95512d773cc1969e3ee4a4b771609145
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